Solvĕre is a consulting firm specialising in providing technical advice on transport, water, hospitals and public service infrastructure projects developed under Public-Private Partnership (PPP) schemes. Its professional services include due diligence for loan and secondary market transactions, risk analysis, CAPEX/OPEX studies, feasibility studies and payment mechanism models. With experience of working in more than 30 countries, the Solvĕre partners provide advisory services to governments, public agencies, private contractors, lenders and investors in the infrastructure sector.
Payment Mechanisms in PPPs
Recent practice in PPP transport projects has seen the participating governments and public agencies gradually moving from demand-based contracts towards availability-based contracts. In these availability-based agreements, the public partner bears the demand risk (i.e. the financial implications caused by actual demand being either over or under that forecast), while risks associated with construction and service availability are transferred to the private partner fulfilling the contract.
Availability-based payment contracts see the public sponsor pay the private partner a pre-established maximum periodic payment for the initial investment and the provision of project facilities. The ‘payment mechanism’ is the contractual agreement that determines how much and at what intervals the government pays the contractor. It is based on Key Performance Indicators (KPIs), and relates to the quality of the service provided by the private partner in terms of how the infrastructure built meets the specific criteria that it must fulfil, as well as the ongoing monitoring and maintenance it requires.
Throughout the lifecycle of the project, the private partner is evaluated on its performance and the availability of facilities and services. Consequently, each periodic payment is adjusted to reflect:
- Deductions for non-compliance with pre-established service levels
- Credits for enhanced performance
The private partner’s revenue is therefore dependent on its performance score and the incentive or penalty rules of the contract.
Using a specific Key Performance Indicator (Indicator 1) as an example, this graph shows the expected penalties linked to the probability of its occurence (one of the main results of the analysis with @RISK)
Payment Mechanism Analysis Using @RISK
To estimate the performance and to forecast the potential deductions in the payment mechanism for each project, Solvĕre has developed its own methodology based on Monte Carlo simulation using Palisade’s risk analysis software, @RISK. This provides advanced analysis to enable all parties involved in infrastructure PPPs to account for each element of the project that can affect its financial status and therefore profitability.
Using @RISK Enables Solvĕre to Provide Consultancy Services, Including:
- Support for governments and public agencies in the design of payment mechanisms and performance indicators at the investment planning and bidding stages.
- Advice for contractors in estimating of payment deduction risk, revenue forecasting and CAPEX/OPEX (initial investment/operation expenditure) balance throughout the life of the contract.
- Due diligence review of the payment mechanisms for lenders and investors in loan or secondary market asset transactions.
Solvĕre Methodology Using @RISK
The key objective is to quantify, for various levels of probability, the economic impact of the performance criteria not being met. Solvĕre’s model takes into account the contract specifications and the resources committed by the operator to complete the project and undertake maintenance of the infrastructure, combining them in order to evaluate the expected level of performance on this base scenario.
Determining 'Performance Probability' with @RISK
Solvĕre builds a specific model for each project and its associated payment mechanism, which is broken down into the main variables that could potentially have an impact on the outcome. The @RISK model is used to determine the ‘performance probability’ function – i.e. the likelihood of an event occurring that will affect the performance and by how much. Inputs for the model are based on empirical laws, historical data series and expert criteria.
For example, the maintenance of a highway in winter may require the use of a certain number of snow-clearing machines to ensure that every carriageway is available and is safe for traffic, according to the requirements of the contract. The private partner operator needs to quantify and factor in the likelihood of being penalised if it does not have the minimum number of machines that will ensure it achieves the performance requirements of the project.
Taking another example, a critical parameter in the quality of road surfaces is the International Roughness Index (IRI). The following graph shows how the behaviour of this variable can be accurately modelled using a LogNormal function in @RISK.
Once all the relevant indicators have been calibrated and the relationships between them have been established through the correlation matrix, Solvĕre combines them with the contractual structure of the payment mechanism. The model accounts for the time variable (i.e. how the infrastructure evolves physically over time), the impact of maintenance and renewal activities, and the strategic decisions of the operator.
The result of the simulation is an estimated payment deduction profile throughout the life of the contract for each probability level and every CAPEX/OPEX scenario:
Using this graph, the private partner can determine the expected revenues under a certain level of probability (i.e. under its assumed risk profile).
Simplifying Complicated Information with @RISK
“The nature of PPPs makes them highly-complex contracts, with payment mechanisms being subject to a significant degree of uncertainty which needs to be analysed in terms of probability and risk,” explains Laura Cózar, director at Solvĕre. “We identify and analyse the different elements of the process so that informed decisions can be made to ensure the feasibility of the project and a proper risk allocation between the partners. @RISK is a powerful and flexible tool that enables us to manage and present large amounts of complicated information in a way that is easy to understand and act upon.”